The invention relates to a method for detection of pilot tones. Pilot tones are sinusoidal oscillations at a known frequency, which are used, for example, in communications systems, in particular in mobile radio systems. A frequent task that occurs in such mobile radio systems is to search for pilot tones.
For example, in digital mobile radio systems that operate in accordance with the GSM/DCS1800/PCS1900 Standard, the radio traffic is organized into organization channels. For a mobile station to set up a connection to the network via a fixed station, it first needs to detect and search for this organization channel. The organization channel is detected by searching for specific pulse sequences, which identify this organization channel.
In the system cited above, pulse sequences are referred to as frequency correction bursts (FCB) and have a sequence of 148 zeros.
In the system under consideration here, the GMSK modulation method (Gaussian Minimum Shift Keying) is used for transmission. In this case, a carrier frequency FT (for example 900 MHz) is modulated with the signal to be transmitted, that is to say in this case, in particular, also with the FCB signal which is of specific interest. The resultant frequency is FT+67.7 kHz, that is to say 67.7 kHz above the carrier frequency. The FCB pulse sequence of 148 zeros is thus converted to a pure sinusoidal signal. In the baseband, this means that the phase difference between adjacent samples is ideally (without channel distortion or noise) ninety degrees (90xc2x0), if it is assumed that sampling takes place at the bit clock rate (4*67.7=270.8 kHz).
Various methods for FCB searching are known from the prior art. For example, the article xe2x80x9cAnfangssynchronisation der Mobilstation im D-Netzxe2x80x9d [Initial synchronization of mobile stations in the D network] by G. Frank and W. Koch, PKI Tech. Report 1 (1990), pages 43-49 describes one method for FCB searching. In this method, the FCB search starts with a frequency shift by multiplying all the (I,Q) samples of the received signal by exp(xe2x88x92jkΠ/2). Each sample Z at the time k can be represented, as a complex number, in the form Z(k)=I(k)+jQ(k). This means that the received signal is shifted downward by 67.7 kHz, so that its mid-frequency after frequency shifting is 0 Hz. The signal is then low-pass filtered. If this is the FCB signal, then it passes through the filter; other signals are largely suppressed due to their wide bandwidth. The magnitude of the filtered signal is then formed, ideally resulting in an approximately rectangular pulse of the same duration as an FCB signal. In contrast to this, the modulation with random data bits in the rest of the time results in a signal similar to noise. An optimum search filter can be specified for the approximately rectangular pulse. This corresponds to sliding averaging over the time period of an FCB. An FCB is regarded as having been found when the maximum value of the filtered signal exceeds a previously defined threshold. The position of the maximum value marks the end of the detected FCB signal.
The method described in this article has the disadvantage that the maximum value of the filtered signal depends on the instantaneous signal amplitudes, and is therefore subject to severe fading fluctuations. Therefore, adaptive amplitude control is required for a reliable FCB search. The low-pass filter also must have a high Q factor; therefore, its construction is complex. Furthermore, this method is highly sensitive to frequency mistuning between the mobile station and base station. Thus, in practice, the maximum value has to be averaged over a number of observation intervals.
A further method is described in the article xe2x80x9cSynchronisation einer Mobilstation im GSM-System DMCS 900 (D-Netz)xe2x80x9d [Synchronization of a mobile station in the GSM DMCS 900 system (D network)] by H. Neuner, H. Bilitza, S. Gxc3xa4rtner in Frequenz [Frequency] 47 (1993) 3-4, pages 66-72. In this method, the phase difference between every fourth sample of the received signal is evaluated. The method is based on the observation that, ideally, such phase differences are zero for the duration of an FCB signal. Since, as already stated above, the phase difference between two adjacent samples is 90xc2x0, the phase difference between four samples is 4xc3x9790=360xc2x0, or 0xc2x0. Interference (fading) is taken into account with a validity range, which is recalculated for each phase difference. An FCB signal is regarded as having been found when a sufficiently large number of negligibly small phase differences occur.
One problem with this method is determining the position of the FCB signal because only every fourth sample is evaluated. Because the method described here makes it necessary to determine the phase difference between samples, the arctan function must be used in order to calculate the phase of the sample from the quadrature components of the sampled received signal. However, virtually no signal processors provide any hardware support for this, so that the calculation is approximated by a complex series development, which requires a considerable amount of computation time.
A third method from the prior art is a method that was developed by Dr. Ralf Hartmann at Siemens AG, which is similar to the Frank and Koch method. This method uses two frequency-selective filters, one of which filters passes FCB signals at the frequency 67.7 kHz without any attenuation, while the other filter completely blocks FCB signals. Magnitudes, and then sliding averages, are formed from both filtered signals. The quotient of the two averages is then formed, and is compared with a previously defined threshold value. If the quotient is below the threshold value, then an FCB is regarded as having been found. The position of the quotient minimum marks the end of the FCB signal.
This method already has been used successfully in chip sets for GSM mobile telephones. Because the quotient formation process results in insensitivity to amplitude fluctuations, the amplitude control required in the Frank and Koch method is not necessary. However, the division process required for quotient formation likewise still requires a relatively large amount of computation time. Furthermore, the method is sensitive to frequency mistuning. In the event of frequency mistuning, one filter can no longer pass the signal through completely, while the other filter no longer completely blocks the signal. This means that the quotient minimum value rises considerably and the threshold value, which is configured for the best case of minimum frequency mistuning, is no longer suitable, so that the entire FCB search becomes uncertain.
A further method for searching for such pilot tones is known from German Patent Application DE 197 43 191, corresponding to U.S. patent application Ser. No. 09/539,239 filed on Mar. 30, 2000. The inventors are named R. Hartmann and B. Yang and the invention is entitled, xe2x80x9cVerfahren zur Suche nach Pilottxc3x6nen,xe2x80x9d [Method for searching for pilot tones] (date of application Sep. 30, 1997). This method uses what is referred to as differential symbol estimation. In this case, the exact phase differences between successive (I,Q) samples of the received signal are not determined, as in the method by Neuner, Bilitza, and Gartner. Instead of this, all that is investigated is to determine whether the phase differences between successive samples are in the interval (0, Π) or (xe2x88x92Π, 0). Both cases correspond to a transmitted symbol of 1 (xe2x80x9c+1xe2x80x9d) or 0 (xe2x80x9cxe2x88x921xe2x80x9d) from the GMSK modulator. Because a FCB signal has 148 zeros is changed to 147 ones after differential coding at the transmitter end, and a virtually equal number of ones and zeros occur outside the FCB signal, then it is possible to search for an FCB signal by searching for a long, cohesive block of ones.
The advantage of the differential symbol estimation is its simple implementation. If I(k) represents the in-phase component and Q(k) represents the quadrature component of the baseband sample at the time k, then, in this method, the mathematical sign of the expression Q(k)*I(kxe2x88x921)xe2x88x92I(k)*Q(kxe2x88x921) ideally reflects the transmitted signal exactly. Because fading of the sampled signal occasionally leads to false symbol estimates, the estimated symbols (1 or 0) are filtered using what is referred to as a match filter. This means that a search window of fixed length is placed over the estimated symbols and the number of ones within the window is counted, in the form of a sliding addition process. The maximum of the signal filtered in this way is then compared with a threshold value, and the presence of an FCB signal is deduced if the threshold value is exceeded.
This additional filtering makes the method described there for searching for pilot tones relatively insensitive to amplitude fluctuations, to a poor signal-to-noise ratio and to frequency mistuning. However, interference from an adjacent channel does represent a problem with this algorithm. If nothing is currently being transmitted in the frequency channel on which a search is currently being carried out for a pilot tone, that is to say for an FCB signal, but a powerful broadband signal is being transmitted on the adjacent channel, then residues from this signal can frequently also be found in the frequency channel to be investigated. This residual signal can then be confused with a pilot tone in the form of an FCB pulse sequence in the investigated frequency channel.
It is accordingly an object of the invention to provide a method for detection of pilot tones that overcomes the hereinafore-mentioned disadvantages of the heretofore-known devices of this general type and that improves the above method of differential symbol estimation such that it is not sensitive to interference from adjacent channels.
With the foregoing and other objects in view, there is provided, in accordance with the invention, a method for identification of a pulse in a signal. The first step of the method is obtaining samples of a signal at successive times k. The sample times has a time difference of xcex94kxe2x89xa72 between the sample times k. The signal includes a pulse sequence having known values 0 and 1 and a known length. The next step is corresponding an estimated symbol xe2x80x9c1xe2x80x9d to a phase difference of the signal when the phase difference is in a range mod (xcex94k*Π/2.2) xe2x88x92Π/2 to mod (xcex94k*Π/2.2Π)+Π/2, and corresponding an estimated symbol xe2x80x9c0xe2x80x9d to the phase difference when the phase difference is not in the range. The next step is filtering the estimated symbols by placing a search window with a search window length equal to the known length of the pulse sequence to be identified minus (xcex94k+1) over the successively estimated symbols, and by in each case forming a symbol sum of the estimated symbols within the search window. The next step is comparing the symbol sum with a sum threshold value. The next step is indicating a sought pulse sequence and a timing of the sought pulse sequence when the symbol sum is at least equal to the sum threshold value.
In accordance with a further mode of the invention, the method includes, before obtaining samples, subjecting the samples to DC voltage compensation.
In accordance with a further mode of the invention, in the method, xcex94k equals 2.
In accordance with a further mode of the invention, in the method, xcex94k equals 5.
In accordance with a further mode of the invention, the pulse sequence to be identified is a sequence of 148 zeros. Such a pulse sequence can identify an organization channel in a mobile radio system.
In accordance with a further object of the invention, the timing of the sought pulse sequence occurs midway between a first time and last time at which the symbol sum exceeds the sum threshold value.
The method according to the invention uses the idea of undersampling, in which, instead of using successive (I,Q) samples, samples located further apart from one another are used to calculate the phase differences. Such undersampling artificially increases overlapping (aliasing) of the residual signal spectra from an adjacent channel. This aliasing changes an originally colored residual signal spectrum to an approximately white spectrum. The residual signal thus behaves like noise and then has scarcely any similarity with the sought FCB signal. The FCB signal itself has a narrowband spectrum that is scarcely influenced by the aliasing effect.
Other features which are considered as characteristic for the invention are set forth in the appended claims.
Although the invention is illustrated and described herein as embodied in a method for detection of pilot tones, it is nevertheless not intended to be limited to the details shown, since various modifications and structural changes may be made therein without departing from the spirit of the invention and within the scope and range of equivalents of the claims.